Ensuring the security and confidentiality of cloud
computing workloads is essential. To this end, major cloud
providers offer computing instances based on trusted execution
environments (TEEs) to support confidential computing in vir-
tual machines. TEEs are hardware-based shielded environments...
04b Atto di convegno in volume
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Glider pilots are confronted with several challenges specific to this kind of flight, the major one being the need to maintain adequate separation from other gliders while still operating theaircraft effectively and safely. In this paper, we present an XR intelligent interface, GlideRX, to help...
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Data preparation has an important role in data analysis, and it is time and resource-consuming, both in terms of human and computational resources. The "Discount quality for responsible data science" project aims to focus on data-quality-based data preparation, analyzing the main characteristics of...
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Cancer disparities are adverse differences in cancer measures that exist among certain population groups. Given that the role they play not only in the disease prognosis but also in therapy response, there is an urgent need to understand what causes them. Most studies investigate these disparities...
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Global network alignment is the computational problem of determining the similarity between nodes of different networks to establish a one-to-one correspondence between them. It has important applications in the biological field, particularly for discovering similar roles between the elements of...
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Radiomics represents a specialized branch of medical imaging where quantitative features are extracted from images. Performing a classification using radiomics means solving two common problems: the imbalanced setting, and the large number of features that would increase the risk of overfitting....
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Drug repositioning is a promising strategy to discover new therapeutic applications for existing drugs, significantly reducing the time and costs associated with traditional drug development. This study employs a network medicine approach to analyze successful cases of drug repositioning, focusing...
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Several recent approaches in reinforcement learning are studying a conceptual architecture where the environment is simultaneously represented at two (or more) levels of abstraction, with the environment providing two traces of data/events/features/fluents, one at a lower-level/finer grain and one...
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Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past frames. Traditional methods, which use recurrent neural networks to capture temporal patterns, have proven their...
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The increasing prevalence of audio deepfakes has raised serious concerns due to their potential misuse in identity theft, disinformation, and the compromise of voice authentication systems. Detecting these manipulations requires models capable of handling a wide range of audio features and attack...